Convection is usually parameterized in global climate models, and there are often large discrepancies between results obtained with different convection schemes. Conventional methods of comparing convection schemes using observational cases or directly in 3D models do not always clearly identify parameterization strengths and weaknesses. In this paper we evaluate the response of parameterizations to various perturbations rather than their behavior under particular strong forcing. We use the linear response function method proposed by Kuang (2010) to compare twelve physical packages in five atmospheric models using single-column model (SCM) simulations under idealized radiative-convective equilibrium conditions. The models are forced with anomalous temperature and moisture tendencies. The temperature and moisture departures from equilibrium are compared with published results from a cloud-resolving model (CRM). Results show that the procedure is capable of isolating the behavior of a convection scheme from other physics schemes. We identify areas of agreement but also substantial differences between convection schemes, some of which can be related to scheme design. Some aspects of the model linear responses are related to their RCE profiles (the relative humidity profile in particular), while others constitute independent diagnostics. All the SCMs show irregularities or discontinuities in behavior that are likely related to switches or thresholds built into the convection schemes, and which do not appear in the CRM. Our results highlight potential flaws in convection schemes and suggest possible new directions to explore for parameterization evaluation.

Single-column models (SCMs) are often used to evaluate model physics and aid parameterization development. However, few studies have systematically compared the results obtained using 1D setups with those of their corresponding 3D models, and examined what factors potentially impact their comparability. This paper addresses these questions. We focus on the application of SCMs under idealized RCE conditions and use a multi-column model (MCM) setup as stepping stone for a 3D model. We find that convective organization in the MCM depends at least as much on the convection scheme used as on other mechanisms known to organize convection (e.g., radiative feedback). Moreover, convective organization emerges as a robust factor affecting SCM-MCM comparability, with more aggregated states in 3D associated with larger behavior deviations from the 1D counterpart. This is found across five convection schemes and applies to simulated mean states, linear responses to small tendency perturbations, and adjustments to doubled-CO2 forcing. Applying a “model-as-truth” approach, we find that even when convection is organized, behavior differences between pairs of schemes in the SCM are largely preserved in the MCM. This indicates that when model physics produces accurate behavior in a 1D setup, it will be more likely to do so in a 3D setup. We also demonstrate the practical value of linear responses by showing that they can accurately predict an SCM’s tropospheric adjustment to doubled-CO2 forcing.